Short-term load forecasting using a chaotic time series

A new approach to short-term load forecasting (STLF) in power systems is described in this paper. The method uses a chaotic time series and artificial neural network. The paper describes chaos time series analysis of daily power system peak loads. Nonlinear mapping of deterministic chaos is identifi...

Full description

Saved in:
Bibliographic Details
Main Authors: Michanos, S.P., Tsakoumis, A.C., Fessas, P., Vladov, S.S., Mladenov, V.M.
Format: Conference Proceeding
Language:English
Citations: Items that cite this one
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c222t-ac914234a4f0231ea31ff0e704a5be4e30201cce58ccad16305e1accb5eee653
cites
container_end_page 440 vol.2
container_issue
container_start_page 437
container_title
container_volume 2
creator Michanos, S.P.
Tsakoumis, A.C.
Fessas, P.
Vladov, S.S.
Mladenov, V.M.
description A new approach to short-term load forecasting (STLF) in power systems is described in this paper. The method uses a chaotic time series and artificial neural network. The paper describes chaos time series analysis of daily power system peak loads. Nonlinear mapping of deterministic chaos is identified by multilayer perceptron (MLP). Using embedding dimension and delay time, an attractor in pseudo phase plane and an ANN model trained by this attractor are constructed. The proposed approach is demonstrated by an example.
doi_str_mv 10.1109/SCS.2003.1227083
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5731316</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5731316</ieee_id><sourcerecordid>5731316</sourcerecordid><originalsourceid>FETCH-LOGICAL-c222t-ac914234a4f0231ea31ff0e704a5be4e30201cce58ccad16305e1accb5eee653</originalsourceid><addsrcrecordid>eNotjM1qwzAQhAWl0JL6XshFL2B3pZUs61hM_yCQg3MPG2WdqMR1kdRD374u7TDMx8AwQtwraJQC_zD0Q6MBsFFaO-jwSlTedbAYnXfe3Igq53dYhL61Ld4KN5znVOrCaZKXmY5ynBMHyiV-nORX_k2S4UxziUGWOLHMnCLnO3E90iVz9c-V2D0_7frXerN9eesfN3XQWpeagldGoyEzgkbFhGocgR0Ysgc2jKBBhcC2C4GOqkWwrCiEg2Xm1uJKrP9u49L3nylOlL731qHCZfwDGeBE4g</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Short-term load forecasting using a chaotic time series</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Michanos, S.P. ; Tsakoumis, A.C. ; Fessas, P. ; Vladov, S.S. ; Mladenov, V.M.</creator><creatorcontrib>Michanos, S.P. ; Tsakoumis, A.C. ; Fessas, P. ; Vladov, S.S. ; Mladenov, V.M.</creatorcontrib><description>A new approach to short-term load forecasting (STLF) in power systems is described in this paper. The method uses a chaotic time series and artificial neural network. The paper describes chaos time series analysis of daily power system peak loads. Nonlinear mapping of deterministic chaos is identified by multilayer perceptron (MLP). Using embedding dimension and delay time, an attractor in pseudo phase plane and an ANN model trained by this attractor are constructed. The proposed approach is demonstrated by an example.</description><identifier>ISBN: 9780780379794</identifier><identifier>ISBN: 0780379799</identifier><identifier>DOI: 10.1109/SCS.2003.1227083</identifier><language>eng</language><ispartof>Signals, Circuits and Systems, 2003. SCS 2003. International Symposium on, 2003, Vol.2, p.437-440 vol.2</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c222t-ac914234a4f0231ea31ff0e704a5be4e30201cce58ccad16305e1accb5eee653</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5731316$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,4050,4051,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5731316$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Michanos, S.P.</creatorcontrib><creatorcontrib>Tsakoumis, A.C.</creatorcontrib><creatorcontrib>Fessas, P.</creatorcontrib><creatorcontrib>Vladov, S.S.</creatorcontrib><creatorcontrib>Mladenov, V.M.</creatorcontrib><title>Short-term load forecasting using a chaotic time series</title><title>Signals, Circuits and Systems, 2003. SCS 2003. International Symposium on</title><description>A new approach to short-term load forecasting (STLF) in power systems is described in this paper. The method uses a chaotic time series and artificial neural network. The paper describes chaos time series analysis of daily power system peak loads. Nonlinear mapping of deterministic chaos is identified by multilayer perceptron (MLP). Using embedding dimension and delay time, an attractor in pseudo phase plane and an ANN model trained by this attractor are constructed. The proposed approach is demonstrated by an example.</description><isbn>9780780379794</isbn><isbn>0780379799</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2003</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotjM1qwzAQhAWl0JL6XshFL2B3pZUs61hM_yCQg3MPG2WdqMR1kdRD374u7TDMx8AwQtwraJQC_zD0Q6MBsFFaO-jwSlTedbAYnXfe3Igq53dYhL61Ld4KN5znVOrCaZKXmY5ynBMHyiV-nORX_k2S4UxziUGWOLHMnCLnO3E90iVz9c-V2D0_7frXerN9eesfN3XQWpeagldGoyEzgkbFhGocgR0Ysgc2jKBBhcC2C4GOqkWwrCiEg2Xm1uJKrP9u49L3nylOlL731qHCZfwDGeBE4g</recordid><startdate>2003</startdate><enddate>2003</enddate><creator>Michanos, S.P.</creator><creator>Tsakoumis, A.C.</creator><creator>Fessas, P.</creator><creator>Vladov, S.S.</creator><creator>Mladenov, V.M.</creator><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2003</creationdate><title>Short-term load forecasting using a chaotic time series</title><author>Michanos, S.P. ; Tsakoumis, A.C. ; Fessas, P. ; Vladov, S.S. ; Mladenov, V.M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c222t-ac914234a4f0231ea31ff0e704a5be4e30201cce58ccad16305e1accb5eee653</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2003</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Michanos, S.P.</creatorcontrib><creatorcontrib>Tsakoumis, A.C.</creatorcontrib><creatorcontrib>Fessas, P.</creatorcontrib><creatorcontrib>Vladov, S.S.</creatorcontrib><creatorcontrib>Mladenov, V.M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Michanos, S.P.</au><au>Tsakoumis, A.C.</au><au>Fessas, P.</au><au>Vladov, S.S.</au><au>Mladenov, V.M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Short-term load forecasting using a chaotic time series</atitle><btitle>Signals, Circuits and Systems, 2003. SCS 2003. International Symposium on</btitle><date>2003</date><risdate>2003</risdate><volume>2</volume><spage>437</spage><epage>440 vol.2</epage><pages>437-440 vol.2</pages><isbn>9780780379794</isbn><isbn>0780379799</isbn><abstract>A new approach to short-term load forecasting (STLF) in power systems is described in this paper. The method uses a chaotic time series and artificial neural network. The paper describes chaos time series analysis of daily power system peak loads. Nonlinear mapping of deterministic chaos is identified by multilayer perceptron (MLP). Using embedding dimension and delay time, an attractor in pseudo phase plane and an ANN model trained by this attractor are constructed. The proposed approach is demonstrated by an example.</abstract><doi>10.1109/SCS.2003.1227083</doi></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 9780780379794
ispartof Signals, Circuits and Systems, 2003. SCS 2003. International Symposium on, 2003, Vol.2, p.437-440 vol.2
issn
language eng
recordid cdi_ieee_primary_5731316
source IEEE Electronic Library (IEL) Conference Proceedings
title Short-term load forecasting using a chaotic time series
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T13%3A18%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Short-term%20load%20forecasting%20using%20a%20chaotic%20time%20series&rft.btitle=Signals,%20Circuits%20and%20Systems,%202003.%20SCS%202003.%20International%20Symposium%20on&rft.au=Michanos,%20S.P.&rft.date=2003&rft.volume=2&rft.spage=437&rft.epage=440%20vol.2&rft.pages=437-440%20vol.2&rft.isbn=9780780379794&rft.isbn_list=0780379799&rft_id=info:doi/10.1109/SCS.2003.1227083&rft_dat=%3Cieee_6IE%3E5731316%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c222t-ac914234a4f0231ea31ff0e704a5be4e30201cce58ccad16305e1accb5eee653%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5731316&rfr_iscdi=true